S-SOMAS Pilot-0 CFA and IRT
Douglas Whitaker
01 November 2021
CFA
This draws on Matt’s code for reading the data and the like.
Reading in the Data
We read in the datasets created using the pilot0_data_cleaning.Rmd file.
We now drop the “nrc” columns because we won’t use them.
Item Response Theory Analysis
This section will start by closely following Mair (2018) Chapter 4.
Dimensionality
## $prlin_list
## $prlin_list$Belief
## Call:
## Gifi::princals(data = dat[, grepl(scale.names[i], names(dat))],
## knots = knotsexp, degrees = 1)
##
## Loss value: 0.772
## Number of iterations: 23
##
## Eigenvalues: 3.156 1.404
##
##
## $prlin_list$Intrinsic
## Call:
## Gifi::princals(data = dat[, grepl(scale.names[i], names(dat))],
## knots = knotsexp, degrees = 1)
##
## Loss value: 0.643
## Number of iterations: 15
##
## Eigenvalues: 4.343 0.655
##
##
## $prlin_list$Extrinsic
## Call:
## Gifi::princals(data = dat[, grepl(scale.names[i], names(dat))],
## knots = knotsexp, degrees = 1)
##
## Loss value: 0.731
## Number of iterations: 13
##
## Eigenvalues: 2.956 1.347
##
##
## $prlin_list$Utility
## Call:
## Gifi::princals(data = dat[, grepl(scale.names[i], names(dat))],
## knots = knotsexp, degrees = 1)
##
## Loss value: 0.671
## Number of iterations: 10
##
## Eigenvalues: 4.265 1.005
##
##
## $prlin_list$Attain
## Call:
## Gifi::princals(data = dat[, grepl(scale.names[i], names(dat))],
## knots = knotsexp, degrees = 1)
##
## Loss value: 0.723
## Number of iterations: 15
##
## Eigenvalues: 2.574 1.298
##
##
## $prlin_list$Interest
## Call:
## Gifi::princals(data = dat[, grepl(scale.names[i], names(dat))],
## knots = knotsexp, degrees = 1)
##
## Loss value: 0.64
## Number of iterations: 10
##
## Eigenvalues: 5.515 0.963
## $prlin_list
## $prlin_list$AcadSC
## Call:
## Gifi::princals(data = dat[, grepl(scale.names[i], names(dat))],
## knots = knotsexp, degrees = 1)
##
## Loss value: 0.738
## Number of iterations: 21
##
## Eigenvalues: 3.569 1.146
##
##
## $prlin_list$Attain
## Call:
## Gifi::princals(data = dat[, grepl(scale.names[i], names(dat))],
## knots = knotsexp, degrees = 1)
##
## Loss value: 0.713
## Number of iterations: 12
##
## Eigenvalues: 2.521 1.503
##
##
## $prlin_list$StatSC
## Call:
## Gifi::princals(data = dat[, grepl(scale.names[i], names(dat))],
## knots = knotsexp, degrees = 1)
##
## Loss value: 0.697
## Number of iterations: 37
##
## Eigenvalues: 4.573 0.881
##
##
## $prlin_list$Difficult
## Call:
## Gifi::princals(data = dat[, grepl(scale.names[i], names(dat))],
## knots = knotsexp, degrees = 1)
##
## Loss value: 0.7
## Number of iterations: 34
##
## Eigenvalues: 3.234 0.97
##
##
## $prlin_list$Expectancy
## Call:
## Gifi::princals(data = dat[, grepl(scale.names[i], names(dat))],
## knots = knotsexp, degrees = 1)
##
## Loss value: 0.76
## Number of iterations: 35
##
## Eigenvalues: 4.254 1.026
##
##
## $prlin_list$Cost
## Call:
## Gifi::princals(data = dat[, grepl(scale.names[i], names(dat))],
## knots = knotsexp, degrees = 1)
##
## Loss value: 0.671
## Number of iterations: 51
##
## Eigenvalues: 3.685 0.919The following items should be dropped based on the results:
- Group 1
- Belief: two groups
- 2rc, 4rc, 5rc, 10rc
- 1, 3rc, 6, 7, 8, 9
- Intrinsic: three groups
- 3, 5, 7
- 4
- 1, 2, 6
- Extrinsic: three groups
- 6, 7, 8
- 1, 4, 5
- 2, 3
- Utility: three groups
- 1, 3rc, 5rc, 8rc
- 2, 4, 6, 7
- Attain: perhaps three groups
- 1, 2, 3
- 4
- 5, 6, 7
- Interest: two groups
- 2, 4, 6, 9
- 1rc, 3rc, 5, 7rc, 8rc
- Belief: two groups
- Group 2
- AcadSC: two groups
- 1, 2, 3, 4, 6
- 5rc, 7rc, 8rc, 9rc
- Attain: perhaps three groups
- 1, 2, 3
- 4
- 5, 6, 7
- StatSC: one group
- Difficulty: perhaps two groups
- 1rc, 2, 3, 6rc, 7rc
- 4rc, 5
- Expectancy: two groups
- 1rc, 6rc, 11rc
- 2, 3, 4, 5, 7, 8, 9, 10
- Cost: three groups
- 5
- 7rc
- 1, 2, 3rc, 4rc, 6
- AcadSC: two groups
## [1] "===================================="
## [1] "Belief"
## [1] "Fitting GRM"
## [1] "Fitting PCM"
## [1] "Fitting GPCM"## Warning in ltm::gpcm(dat.tmp): Not successful convergence: 127.## [1] "Belief: GPCM preferred based on LR test (to the PCM)."
## [1] "Belief: AIC for PCM = 39311.7206032831"
## [1] "Belief: AIC for GPCM = 37065.202619307"
## [1] "Belief: AIC for GRM = 36752.7727959302"
## [1] "GRM preferred based on AIC"
## [1] "Belief: BIC for PCM = 39615.7086214914"
## [1] "Belief: BIC for GPCM = 37419.8553072166"
## [1] "Belief: BIC for GRM = 37107.4254838398"
## [1] "GRM preferred based on BIC"
## [1] "GRM preferred based on AIC and BIC"
## [1] "===================================="
## [1] "Intrinsic"
## [1] "Fitting GRM"
## [1] "Fitting PCM"
## [1] "Fitting GPCM"
## [1] "Intrinsic: GPCM preferred based on LR test (to the PCM)."
## [1] "Intrinsic: AIC for PCM = 25231.3013600355"
## [1] "Intrinsic: AIC for GPCM = 25189.8952601719"
## [1] "Intrinsic: AIC for GRM = 24973.7007361583"
## [1] "GRM preferred based on AIC"
## [1] "Intrinsic: BIC for PCM = 25444.0929727812"
## [1] "Intrinsic: BIC for GPCM = 25438.1521417086"
## [1] "Intrinsic: BIC for GRM = 25221.957617695"
## [1] "GRM preferred based on BIC"
## [1] "GRM preferred based on AIC and BIC"
## [1] "===================================="
## [1] "Extrinsic"
## [1] "Fitting GRM"
## [1] "Fitting PCM"
## [1] "Fitting GPCM"
## [1] "Extrinsic: GPCM preferred based on LR test (to the PCM)."
## [1] "Extrinsic: AIC for PCM = 30955.0339362373"
## [1] "Extrinsic: AIC for GPCM = 30160.0033902848"
## [1] "Extrinsic: AIC for GRM = 30108.1052547675"
## [1] "GRM preferred based on AIC"
## [1] "Extrinsic: BIC for PCM = 31198.2243508039"
## [1] "Extrinsic: BIC for GPCM = 30443.7255406125"
## [1] "Extrinsic: BIC for GRM = 30391.8274050952"
## [1] "GRM preferred based on BIC"
## [1] "GRM preferred based on AIC and BIC"
## [1] "===================================="
## [1] "Utility"
## [1] "Fitting GRM"
## [1] "Fitting PCM"
## [1] "Fitting GPCM"
## [1] "Utility: GPCM preferred based on LR test (to the PCM)."
## [1] "Utility: AIC for PCM = 28411.2428029154"
## [1] "Utility: AIC for GPCM = 28300.662281937"
## [1] "Utility: AIC for GRM = 27900.2648929763"
## [1] "GRM preferred based on AIC"
## [1] "Utility: BIC for PCM = 28654.433217482"
## [1] "Utility: BIC for GPCM = 28584.3844322646"
## [1] "Utility: BIC for GRM = 28183.987043304"
## [1] "GRM preferred based on BIC"
## [1] "GRM preferred based on AIC and BIC"
## [1] "===================================="
## [1] "Attain"
## [1] "Fitting GRM"
## [1] "Fitting PCM"
## [1] "Fitting GPCM"
## [1] "Attain: GPCM preferred based on LR test (to the PCM)."
## [1] "Attain: AIC for PCM = 28845.8115121386"
## [1] "Attain: AIC for GPCM = 27921.2078403712"
## [1] "Attain: AIC for GRM = 27819.5287214923"
## [1] "GRM preferred based on AIC"
## [1] "Attain: BIC for PCM = 29058.6031248843"
## [1] "Attain: BIC for GPCM = 28169.4647219079"
## [1] "Attain: BIC for GRM = 28067.785603029"
## [1] "GRM preferred based on BIC"
## [1] "GRM preferred based on AIC and BIC"
## [1] "===================================="
## [1] "Interest"
## [1] "Fitting GRM"
## [1] "Fitting PCM"
## [1] "Fitting GPCM"
## [1] "Interest: GPCM preferred based on LR test (to the PCM)."
## [1] "Interest: AIC for PCM = 33196.855729489"
## [1] "Interest: AIC for GPCM = 32920.7951625924"
## [1] "Interest: AIC for GRM = 32356.0605503125"
## [1] "GRM preferred based on AIC"
## [1] "Interest: BIC for PCM = 33470.4449458764"
## [1] "Interest: BIC for GPCM = 33239.982581711"
## [1] "Interest: BIC for GRM = 32675.2479694311"
## [1] "GRM preferred based on BIC"
## [1] "GRM preferred based on AIC and BIC"## [1] "===================================="
## [1] "AcadSC"
## [1] "Fitting GRM"
## [1] "Fitting PCM"
## [1] "Fitting GPCM"## Warning in ltm::gpcm(dat.tmp): Not successful convergence: 105.## [1] "AcadSC: GPCM preferred based on LR test (to the PCM)."
## [1] "AcadSC: AIC for PCM = 28999.6612904891"
## [1] "AcadSC: AIC for GPCM = 28592.1363435735"
## [1] "AcadSC: AIC for GRM = 28318.0139962465"
## [1] "GRM preferred based on AIC"
## [1] "AcadSC: BIC for PCM = 29273.3885555243"
## [1] "AcadSC: BIC for GPCM = 28911.484819448"
## [1] "AcadSC: BIC for GRM = 28637.3624721209"
## [1] "GRM preferred based on BIC"
## [1] "GRM preferred based on AIC and BIC"
## [1] "===================================="
## [1] "Attain"
## [1] "Fitting GRM"
## [1] "Fitting PCM"
## [1] "Fitting GPCM"
## [1] "Attain: GPCM preferred based on LR test (to the PCM)."
## [1] "Attain: AIC for PCM = 28752.4413562791"
## [1] "Attain: AIC for GPCM = 27592.5587563126"
## [1] "Attain: AIC for GRM = 27523.0487058624"
## [1] "GRM preferred based on AIC"
## [1] "Attain: BIC for PCM = 28965.3403401954"
## [1] "Attain: BIC for GPCM = 27840.9409042149"
## [1] "Attain: BIC for GRM = 27771.4308537647"
## [1] "GRM preferred based on BIC"
## [1] "GRM preferred based on AIC and BIC"
## [1] "===================================="
## [1] "StatSC"
## [1] "Fitting GRM"
## [1] "Fitting PCM"
## [1] "Fitting GPCM"
## [1] "StatSC: GPCM preferred based on LR test (to the PCM)."
## [1] "StatSC: AIC for PCM = 32013.0589225334"
## [1] "StatSC: AIC for GPCM = 31717.1834206367"
## [1] "StatSC: AIC for GRM = 31504.6465825815"
## [1] "GRM preferred based on AIC"
## [1] "StatSC: BIC for PCM = 32286.7861875687"
## [1] "StatSC: BIC for GPCM = 32036.5318965111"
## [1] "StatSC: BIC for GRM = 31823.9950584559"
## [1] "GRM preferred based on BIC"
## [1] "GRM preferred based on AIC and BIC"
## [1] "===================================="
## [1] "Difficult"
## [1] "Fitting GRM"
## [1] "Fitting PCM"
## [1] "Fitting GPCM"
## [1] "Difficult: GPCM preferred based on LR test (to the PCM)."
## [1] "Difficult: AIC for PCM = 26567.1562385134"
## [1] "Difficult: AIC for GPCM = 26114.158648926"
## [1] "Difficult: AIC for GRM = 25982.2337043468"
## [1] "GRM preferred based on AIC"
## [1] "Difficult: BIC for PCM = 26780.0552224296"
## [1] "Difficult: BIC for GPCM = 26362.5407968284"
## [1] "Difficult: BIC for GRM = 26230.6158522491"
## [1] "GRM preferred based on BIC"
## [1] "GRM preferred based on AIC and BIC"
## [1] "===================================="
## [1] "Expectancy"
## [1] "Fitting GRM"
## [1] "Fitting PCM"
## [1] "Fitting GPCM"
## [1] "Expectancy: GPCM preferred based on LR test (to the PCM)."
## [1] "Expectancy: AIC for PCM = 38569.7468932551"
## [1] "Expectancy: AIC for GPCM = 38126.8138233815"
## [1] "Expectancy: AIC for GRM = 37798.4546486401"
## [1] "GRM preferred based on AIC"
## [1] "Expectancy: BIC for PCM = 38904.3024394093"
## [1] "Expectancy: BIC for GPCM = 38517.128627228"
## [1] "Expectancy: BIC for GRM = 38188.7694524866"
## [1] "GRM preferred based on BIC"
## [1] "GRM preferred based on AIC and BIC"
## [1] "===================================="
## [1] "Cost"
## [1] "Fitting GRM"
## [1] "Fitting PCM"
## [1] "Fitting GPCM"
## [1] "Cost: GPCM preferred based on LR test (to the PCM)."
## [1] "Cost: AIC for PCM = 26686.3887450126"
## [1] "Cost: AIC for GPCM = 26252.2728510383"
## [1] "Cost: AIC for GRM = 26046.7487960303"
## [1] "GRM preferred based on AIC"
## [1] "Cost: BIC for PCM = 26899.2877289289"
## [1] "Cost: BIC for GPCM = 26500.6549989407"
## [1] "Cost: BIC for GRM = 26295.1309439327"
## [1] "GRM preferred based on BIC"
## [1] "GRM preferred based on AIC and BIC"| item | outfit | z.outfit | infit | z.infit | S_X2 | df.S_X2 | RMSEA.S_X2 | p.S_X2 |
|---|---|---|---|---|---|---|---|---|
| Belief_1 | 0.9083373 | -1.6936425 | 0.8745332 | -2.5503835 | 149.05323 | 107 | 0.0183202 | 0.0045209 |
| Belief_2rc | 0.9998365 | 0.0055966 | 0.9997730 | 0.0036146 | 143.97737 | 146 | 0.0000000 | 0.5318197 |
| Belief_3rc | 1.1016261 | 1.6802583 | 0.9672486 | -0.6376904 | 130.22594 | 103 | 0.0150243 | 0.0361576 |
| Belief_4rc | 1.0103483 | 0.3283426 | 1.0054998 | 0.1805490 | 193.54223 | 132 | 0.0199536 | 0.0003893 |
| Belief_5rc | 1.0001663 | 0.0162170 | 0.9995149 | -0.0029613 | 181.06521 | 151 | 0.0130396 | 0.0479821 |
| Belief_6 | 0.9517347 | -0.8175157 | 0.8817963 | -2.1176724 | 120.13443 | 93 | 0.0157848 | 0.0306473 |
| Belief_7 | 0.8821675 | -1.9135571 | 0.8761257 | -2.1442445 | 90.87173 | 85 | 0.0076806 | 0.3116276 |
| Belief_8 | 0.9271236 | -1.0637218 | 0.9314208 | -1.0228932 | 133.92857 | 90 | 0.0204161 | 0.0018454 |
| Belief_9 | 0.8536343 | -2.6464732 | 0.8715846 | -2.4058504 | 126.87179 | 103 | 0.0140684 | 0.0553164 |
| Belief_10rc | 0.9978476 | -0.0618087 | 0.9977606 | -0.0647792 | 198.72471 | 149 | 0.0168816 | 0.0040424 |
| Intrinsic_1 | 0.9560248 | -0.7748749 | 0.8904845 | -2.3628270 | 96.60992 | 99 | 0.0000000 | 0.5492416 |
| Intrinsic_2 | 0.8773300 | -2.3189473 | 0.8963590 | -2.2246359 | 130.35669 | 110 | 0.0125713 | 0.0900895 |
| Intrinsic_3 | 0.8293959 | -3.3139106 | 0.8543568 | -3.0272872 | 83.44789 | 89 | 0.0000000 | 0.6461220 |
| Intrinsic_4 | 0.8810396 | -2.3017103 | 0.8827254 | -2.5082766 | 114.62498 | 98 | 0.0120362 | 0.1203374 |
| Intrinsic_5 | 0.8984186 | -2.0188935 | 0.8867552 | -2.4824198 | 122.16802 | 96 | 0.0152571 | 0.0369652 |
| Intrinsic_6 | 0.8797606 | -2.3087878 | 0.8944218 | -2.5289181 | 111.40346 | 100 | 0.0098682 | 0.2048798 |
| Intrinsic_7 | 0.8859903 | -2.0757220 | 0.8911516 | -2.2235199 | 134.99232 | 103 | 0.0162864 | 0.0188503 |
| Extrinsic_1 | 0.8102723 | -3.7181299 | 0.8396056 | -3.4335708 | 120.65046 | 111 | 0.0086166 | 0.2500693 |
| Extrinsic_2 | 0.9176694 | -1.6530776 | 0.9458213 | -1.1478379 | 214.06011 | 147 | 0.0197376 | 0.0002557 |
| Extrinsic_3 | 0.9184093 | -1.5040334 | 0.9569747 | -0.8523050 | 140.16969 | 139 | 0.0026807 | 0.4562335 |
| Extrinsic_4 | 0.8136503 | -3.8517401 | 0.7971410 | -4.5651554 | 128.64084 | 108 | 0.0127754 | 0.0855815 |
| Extrinsic_5 | 0.6937860 | -6.1001272 | 0.6995595 | -6.7074287 | 119.82509 | 96 | 0.0145580 | 0.0502953 |
| Extrinsic_6 | 0.9338412 | -1.7504248 | 0.9404056 | -1.6590664 | 128.96770 | 121 | 0.0074989 | 0.2932223 |
| Extrinsic_7 | 0.9427514 | -1.4531009 | 0.9600178 | -1.0877258 | 165.72214 | 141 | 0.0122364 | 0.0759066 |
| Extrinsic_8 | 0.9136457 | -1.6032809 | 0.9561762 | -0.8368909 | 178.45339 | 120 | 0.0203956 | 0.0004297 |
| Utility_1 | 0.8933819 | -1.8910613 | 0.8931276 | -2.1368886 | 123.45723 | 102 | 0.0134032 | 0.0729471 |
| Utility_2 | 1.0165066 | 0.3158584 | 0.9415052 | -1.1704696 | 114.53494 | 121 | 0.0000000 | 0.6480886 |
| Utility_3rc | 0.9347521 | -0.9837964 | 0.8936473 | -2.0546240 | 111.32986 | 96 | 0.0116776 | 0.1356840 |
| Utility_4 | 0.8987338 | -1.7410066 | 0.8785894 | -2.2526897 | 128.46445 | 99 | 0.0159424 | 0.0248519 |
| Utility_5rc | 1.3782258 | 5.6383219 | 1.0128660 | 0.2673682 | 125.83880 | 109 | 0.0114859 | 0.1289980 |
| Utility_6 | 0.9682190 | -0.5777702 | 0.9456005 | -1.0904806 | 130.19154 | 114 | 0.0110132 | 0.1425248 |
| Utility_7 | 0.9817641 | -0.3558544 | 0.9509363 | -1.0735685 | 116.08069 | 119 | 0.0000000 | 0.5586237 |
| Utility_8rc | 1.0246479 | 0.4043017 | 0.9626254 | -0.7324305 | 130.12121 | 108 | 0.0132256 | 0.0724465 |
| Attain_1rc | 0.9611892 | -0.9860154 | 0.9577044 | -1.0949880 | 123.93309 | 114 | 0.0086260 | 0.2471446 |
| Attain_2rc | 0.7812977 | -4.8981223 | 0.7992143 | -5.3131756 | 108.48518 | 103 | 0.0067437 | 0.3365643 |
| Attain_3rc | 0.7287467 | -5.0214768 | 0.7143009 | -6.0456291 | 103.43563 | 97 | 0.0075272 | 0.3085941 |
| Attain_4 | 0.8194747 | -4.2361412 | 0.8314721 | -4.1628449 | 102.92532 | 105 | 0.0000000 | 0.5390414 |
| Attain_5 | 0.9505666 | -0.7909762 | 0.9571279 | -0.7253576 | 159.86204 | 118 | 0.0174057 | 0.0062325 |
| Attain_6 | 0.9229012 | -1.9427080 | 0.9269244 | -1.9389174 | 115.11498 | 120 | 0.0000000 | 0.6089226 |
| Attain_7 | 0.9976777 | -0.0668475 | 0.9938178 | -0.1952460 | 176.19524 | 142 | 0.0143404 | 0.0271330 |
| Interest_1rc | 1.0426400 | 0.8422140 | 1.0067271 | 0.1710960 | 184.18455 | 155 | 0.0126804 | 0.0546919 |
| Interest_2 | 0.9307994 | -1.2323996 | 0.9161723 | -1.8322180 | 124.11891 | 120 | 0.0054140 | 0.3798707 |
| Interest_3rc | 0.9909853 | -0.1237327 | 0.9473488 | -1.1154879 | 112.86304 | 112 | 0.0025652 | 0.4593582 |
| Interest_4 | 0.9509119 | -0.9623967 | 0.9351820 | -1.4578056 | 139.53833 | 132 | 0.0069835 | 0.3098566 |
| Interest_5 | 0.7997963 | -1.7978818 | 0.8472844 | -3.2910023 | 112.13000 | 101 | 0.0097008 | 0.2111116 |
| Interest_6 | 0.9879636 | -0.2115414 | 0.9529608 | -1.0098010 | 182.97559 | 126 | 0.0196508 | 0.0006921 |
| Interest_7rc | 1.4446757 | 7.5886167 | 1.1750784 | 3.8081690 | 268.30384 | 147 | 0.0265461 | 0.0000000 |
| Interest_8rc | 1.2307166 | 3.8484623 | 0.9810139 | -0.4144565 | 157.56207 | 145 | 0.0086014 | 0.2247438 |
| Interest_9 | 0.9620632 | -0.7434025 | 0.9526698 | -1.0939677 | 135.88219 | 134 | 0.0034634 | 0.4383596 |
| item | outfit | z.outfit | infit | z.infit | S_X2 | df.S_X2 | RMSEA.S_X2 | p.S_X2 |
|---|---|---|---|---|---|---|---|---|
| AcadSC_1 | 1.0135368 | 0.1483109 | 0.9724579 | -0.2364549 | 102.51773 | 61 | 0.0240779 | 0.0006971 |
| AcadSC_2 | 0.9422364 | -1.0829594 | 0.9419922 | -1.1310974 | 77.82917 | 84 | 0.0000000 | 0.6687593 |
| AcadSC_3 | 0.9293060 | -1.0687019 | 0.9498574 | -0.7703811 | 74.24581 | 72 | 0.0051545 | 0.4048978 |
| AcadSC_4 | 0.9197887 | -1.4728625 | 0.9321519 | -1.2918976 | 80.72873 | 86 | 0.0000000 | 0.6403239 |
| AcadSC_5rc | 0.9996524 | 0.0068842 | 0.9584833 | -1.0370712 | 106.47552 | 101 | 0.0067954 | 0.3353357 |
| AcadSC_6 | 0.8905609 | -1.5702298 | 0.9373729 | -0.9589105 | 95.33037 | 78 | 0.0137570 | 0.0886976 |
| AcadSC_7rc | 0.8948377 | -1.5374508 | 0.8939398 | -1.8452567 | 73.69678 | 74 | 0.0000000 | 0.4880755 |
| AcadSC_8rc | 0.9574289 | -1.2357586 | 0.9596394 | -1.1942121 | 145.52925 | 109 | 0.0168956 | 0.0111361 |
| AcadSC_9rc | 0.8272627 | -2.0824669 | 0.9057011 | -1.4356420 | 88.62651 | 70 | 0.0150551 | 0.0657570 |
| Attain_1rc | 0.9634807 | -0.9303761 | 0.9621610 | -0.9799001 | 123.77115 | 110 | 0.0103265 | 0.1744242 |
| Attain_2rc | 0.8385981 | -3.8975958 | 0.8460861 | -4.2595309 | 116.65711 | 100 | 0.0119115 | 0.1220743 |
| Attain_3rc | 0.6005479 | -8.1699974 | 0.6337194 | -8.3616910 | 95.45302 | 88 | 0.0084936 | 0.2753849 |
| Attain_4 | 0.8401770 | -3.6078193 | 0.8569057 | -3.3285562 | 124.71324 | 103 | 0.0134002 | 0.0716446 |
| Attain_5 | 0.9401552 | -0.9877468 | 0.9608592 | -0.6674221 | 106.34218 | 105 | 0.0032997 | 0.4450396 |
| Attain_6 | 0.8723513 | -3.0445502 | 0.8842693 | -2.9631540 | 118.49649 | 111 | 0.0075846 | 0.2957209 |
| Attain_7 | 0.9997867 | 0.0023717 | 0.9996636 | -0.0018577 | 166.39507 | 143 | 0.0118048 | 0.0879748 |
| StatSC_1 | 0.9469441 | -1.0050758 | 0.9476705 | -1.1032146 | 121.36563 | 122 | 0.0000000 | 0.4991892 |
| StatSC_2 | 0.7898828 | -4.2473277 | 0.7966599 | -4.5179768 | 100.93881 | 102 | 0.0000000 | 0.5110969 |
| StatSC_3 | 0.8733246 | -2.1641293 | 0.9367211 | -1.1220970 | 147.51844 | 118 | 0.0145973 | 0.0340915 |
| StatSC_4rc | 0.7809108 | -3.7154255 | 0.8108177 | -4.3623962 | 108.43566 | 100 | 0.0084767 | 0.2652186 |
| StatSC_5rc | 0.8486758 | -2.5504583 | 0.9121291 | -1.7634856 | 134.04473 | 116 | 0.0115110 | 0.1206897 |
| StatSC_6 | 0.9352988 | -1.2699613 | 0.9627186 | -0.8021607 | 138.38401 | 144 | 0.0000000 | 0.6163476 |
| StatSC_7rc | 0.8968812 | -2.2054105 | 0.8760044 | -2.9107588 | 115.21881 | 110 | 0.0063570 | 0.3478142 |
| StatSC_8rc | 0.9031984 | -1.9813380 | 0.9045994 | -2.2687630 | 120.03544 | 119 | 0.0027224 | 0.4561557 |
| StatSC_9rc | 0.9056372 | -1.8125412 | 0.9636489 | -0.7427572 | 167.93364 | 130 | 0.0157655 | 0.0140235 |
| Difficult_1rc | 0.8994795 | -1.7972848 | 0.9117084 | -1.7285947 | 132.16610 | 93 | 0.0189400 | 0.0047567 |
| Difficult_2 | 0.9392016 | -1.5293383 | 0.9372037 | -1.6303509 | 118.41825 | 105 | 0.0104332 | 0.1749557 |
| Difficult_3 | 0.6873437 | -5.5397552 | 0.7176398 | -6.8464315 | 103.18080 | 79 | 0.0161468 | 0.0352830 |
| Difficult_4rc | 0.9191751 | -1.7225404 | 0.9485975 | -1.1452820 | 121.70413 | 110 | 0.0095200 | 0.2097455 |
| Difficult_5 | 0.9376760 | -1.5712326 | 0.9446255 | -1.4634357 | 134.41535 | 125 | 0.0080099 | 0.2666179 |
| Difficult_6rc | 0.8459655 | -3.6540789 | 0.8630491 | -3.4127017 | 113.40772 | 93 | 0.0136717 | 0.0739260 |
| Difficult_7rc | 0.7871466 | -3.6531589 | 0.8125721 | -4.0539385 | 91.23919 | 82 | 0.0097966 | 0.2273409 |
| Expectancy_1rc | 0.9749908 | -0.5464644 | 0.9220012 | -1.9514578 | 155.18526 | 130 | 0.0128460 | 0.0652863 |
| Expectancy_2 | 0.9917171 | -0.1204180 | 0.9678448 | -0.5505685 | 94.61783 | 104 | 0.0000000 | 0.7338813 |
| Expectancy_3 | 0.8292210 | -2.8574838 | 0.9021057 | -1.6023107 | 83.21327 | 85 | 0.0000000 | 0.5345681 |
| Expectancy_4 | 0.9332060 | -1.1141467 | 0.9484059 | -0.8738699 | 93.26605 | 100 | 0.0000000 | 0.6699801 |
| Expectancy_5 | 0.9300896 | -1.5991827 | 0.9277239 | -1.7426933 | 113.32235 | 122 | 0.0000000 | 0.7006677 |
| Expectancy_6rc | 0.9660973 | -0.8624339 | 0.9514977 | -1.2911414 | 162.87970 | 140 | 0.0117985 | 0.0903571 |
| Expectancy_7 | 0.9949045 | -0.0957580 | 0.9643615 | -0.8169652 | 152.14021 | 138 | 0.0093423 | 0.1939304 |
| Expectancy_8 | 0.9585065 | -0.6927004 | 0.9448335 | -0.9941490 | 126.17388 | 112 | 0.0103825 | 0.1700656 |
| Expectancy_9 | 0.9404279 | -1.1441411 | 0.9155781 | -1.7568315 | 98.97153 | 115 | 0.0000000 | 0.8567663 |
| Expectancy_10 | 0.8878383 | -1.7358686 | 0.9350613 | -1.0862907 | 146.79025 | 122 | 0.0131561 | 0.0626705 |
| Expectancy_11rc | 1.0452101 | 1.0077141 | 0.9996779 | 0.0058950 | 141.78317 | 134 | 0.0070338 | 0.3060521 |
| Cost_1 | 0.6401537 | -7.0811540 | 0.6714079 | -7.3641188 | 80.85900 | 77 | 0.0065337 | 0.3596280 |
| Cost_2 | 0.8242000 | -3.4187942 | 0.8334123 | -3.3781879 | 75.55022 | 78 | 0.0000000 | 0.5575190 |
| Cost_3rc | 1.0022898 | 0.0683396 | 0.9781998 | -0.5271049 | 111.76055 | 114 | 0.0000000 | 0.5418325 |
| Cost_4rc | 0.9516851 | -1.0803802 | 0.9293816 | -1.6501624 | 108.05241 | 108 | 0.0006429 | 0.4804817 |
| Cost_5rc | 0.9825171 | -0.4017883 | 0.9504320 | -1.2890030 | 131.57313 | 124 | 0.0072126 | 0.3037737 |
| Cost_6 | 0.9240229 | -1.5857455 | 0.9171237 | -1.8623706 | 110.32199 | 99 | 0.0098698 | 0.2053086 |
| Cost_7rc | 0.9313860 | -1.5299768 | 0.9531597 | -1.1592159 | 114.98325 | 128 | 0.0000000 | 0.7883876 |
| item | outfit | z.outfit | infit | z.infit | S_X2 | df.S_X2 | RMSEA.S_X2 | p.S_X2 |
|---|---|---|---|---|---|---|---|---|
| Belief_1 | 0.9069039 | -1.7200545 | 0.8740829 | -2.5593252 | 90.10841 | 71 | 0.0151602 | 0.0625662 |
| Belief_3rc | 1.1083230 | 1.7928611 | 0.9691768 | -0.5999676 | 85.19639 | 73 | 0.0119447 | 0.1556350 |
| Belief_6 | 0.9473761 | -0.8961687 | 0.8774409 | -2.2029555 | 86.61001 | 64 | 0.0173693 | 0.0314704 |
| Belief_7 | 0.8720189 | -2.0925514 | 0.8738243 | -2.1910866 | 77.89723 | 62 | 0.0147974 | 0.0838164 |
| Belief_8 | 0.9219549 | -1.1443943 | 0.9314873 | -1.0232153 | 66.59681 | 68 | 0.0000000 | 0.5254573 |
| Belief_9 | 0.8565927 | -2.5902785 | 0.8762626 | -2.3148009 | 80.03083 | 70 | 0.0110622 | 0.1932216 |
| Intrinsic_1 | 0.9560248 | -0.7748749 | 0.8904845 | -2.3628270 | 96.60992 | 99 | 0.0000000 | 0.5492416 |
| Intrinsic_2 | 0.8773300 | -2.3189473 | 0.8963590 | -2.2246359 | 130.35669 | 110 | 0.0125713 | 0.0900895 |
| Intrinsic_3 | 0.8293959 | -3.3139106 | 0.8543568 | -3.0272872 | 83.44789 | 89 | 0.0000000 | 0.6461220 |
| Intrinsic_4 | 0.8810396 | -2.3017103 | 0.8827254 | -2.5082766 | 114.62498 | 98 | 0.0120362 | 0.1203374 |
| Intrinsic_5 | 0.8984186 | -2.0188935 | 0.8867552 | -2.4824198 | 122.16802 | 96 | 0.0152571 | 0.0369652 |
| Intrinsic_6 | 0.8797606 | -2.3087878 | 0.8944218 | -2.5289181 | 111.40346 | 100 | 0.0098682 | 0.2048798 |
| Intrinsic_7 | 0.8859903 | -2.0757220 | 0.8911516 | -2.2235199 | 134.99232 | 103 | 0.0162864 | 0.0188503 |
| Extrinsic_1 | 0.7823215 | -4.3403026 | 0.8270469 | -3.7090091 | 128.48231 | 80 | 0.0227493 | 0.0004777 |
| Extrinsic_4 | 0.7884206 | -4.4699574 | 0.7795447 | -5.0029897 | 95.55652 | 78 | 0.0138642 | 0.0861812 |
| Extrinsic_5 | 0.6867238 | -6.4794078 | 0.6927442 | -6.9128231 | 129.37786 | 73 | 0.0256811 | 0.0000536 |
| Extrinsic_6 | 0.9192314 | -2.1107833 | 0.9284970 | -1.9763518 | 104.87774 | 94 | 0.0099409 | 0.2081531 |
| Extrinsic_7 | 0.9459849 | -1.3553161 | 0.9589658 | -1.1120190 | 138.82906 | 109 | 0.0152872 | 0.0283908 |
| Extrinsic_8 | 0.9066458 | -1.7174156 | 0.9530168 | -0.8965420 | 138.49241 | 95 | 0.0197727 | 0.0024114 |
| Utility_1 | 0.8933819 | -1.8910613 | 0.8931276 | -2.1368886 | 123.45723 | 102 | 0.0134032 | 0.0729471 |
| Utility_2 | 1.0165066 | 0.3158584 | 0.9415052 | -1.1704696 | 114.53494 | 121 | 0.0000000 | 0.6480886 |
| Utility_3rc | 0.9347521 | -0.9837964 | 0.8936473 | -2.0546240 | 111.32986 | 96 | 0.0116776 | 0.1356840 |
| Utility_4 | 0.8987338 | -1.7410066 | 0.8785894 | -2.2526897 | 128.46445 | 99 | 0.0159424 | 0.0248519 |
| Utility_5rc | 1.3782258 | 5.6383219 | 1.0128660 | 0.2673682 | 125.83880 | 109 | 0.0114859 | 0.1289980 |
| Utility_6 | 0.9682190 | -0.5777702 | 0.9456005 | -1.0904806 | 130.19154 | 114 | 0.0110132 | 0.1425248 |
| Utility_7 | 0.9817641 | -0.3558544 | 0.9509363 | -1.0735685 | 116.08069 | 119 | 0.0000000 | 0.5586237 |
| Utility_8rc | 1.0246479 | 0.4043017 | 0.9626254 | -0.7324305 | 130.12121 | 108 | 0.0132256 | 0.0724465 |
| Attain_4 | 0.8787158 | -3.0969432 | 0.8672025 | -3.5243977 | 76.48363 | 56 | 0.0176738 | 0.0358391 |
| Attain_5 | 0.8340862 | -2.6275243 | 0.8898803 | -1.8858899 | 93.92228 | 57 | 0.0235195 | 0.0015012 |
| Attain_6 | 0.5271114 | -11.5653944 | 0.5348379 | -12.4729606 | 87.98753 | 52 | 0.0243106 | 0.0013439 |
| Attain_7 | 0.9502676 | -1.5078928 | 0.9452052 | -1.6833969 | 78.25299 | 60 | 0.0161181 | 0.0568689 |
| Interest_1rc | 1.0426400 | 0.8422140 | 1.0067271 | 0.1710960 | 184.18455 | 155 | 0.0126804 | 0.0546919 |
| Interest_2 | 0.9307994 | -1.2323996 | 0.9161723 | -1.8322180 | 124.11891 | 120 | 0.0054140 | 0.3798707 |
| Interest_3rc | 0.9909853 | -0.1237327 | 0.9473488 | -1.1154879 | 112.86304 | 112 | 0.0025652 | 0.4593582 |
| Interest_4 | 0.9509119 | -0.9623967 | 0.9351820 | -1.4578056 | 139.53833 | 132 | 0.0069835 | 0.3098566 |
| Interest_5 | 0.7997963 | -1.7978818 | 0.8472844 | -3.2910023 | 112.13000 | 101 | 0.0097008 | 0.2111116 |
| Interest_6 | 0.9879636 | -0.2115414 | 0.9529608 | -1.0098010 | 182.97559 | 126 | 0.0196508 | 0.0006921 |
| Interest_7rc | 1.4446757 | 7.5886167 | 1.1750784 | 3.8081690 | 268.30384 | 147 | 0.0265461 | 0.0000000 |
| Interest_8rc | 1.2307166 | 3.8484623 | 0.9810139 | -0.4144565 | 157.56207 | 145 | 0.0086014 | 0.2247438 |
| Interest_9 | 0.9620632 | -0.7434025 | 0.9526698 | -1.0939677 | 135.88219 | 134 | 0.0034634 | 0.4383596 |
| item | outfit | z.outfit | infit | z.infit | S_X2 | df.S_X2 | RMSEA.S_X2 | p.S_X2 |
|---|---|---|---|---|---|---|---|---|
| AcadSC_1 | 1.0135368 | 0.1483109 | 0.9724579 | -0.2364549 | 102.51773 | 61 | 0.0240779 | 0.0006971 |
| AcadSC_2 | 0.9422364 | -1.0829594 | 0.9419922 | -1.1310974 | 77.82917 | 84 | 0.0000000 | 0.6687593 |
| AcadSC_3 | 0.9293060 | -1.0687019 | 0.9498574 | -0.7703811 | 74.24581 | 72 | 0.0051545 | 0.4048978 |
| AcadSC_4 | 0.9197887 | -1.4728625 | 0.9321519 | -1.2918976 | 80.72873 | 86 | 0.0000000 | 0.6403239 |
| AcadSC_5rc | 0.9996524 | 0.0068842 | 0.9584833 | -1.0370712 | 106.47552 | 101 | 0.0067954 | 0.3353357 |
| AcadSC_6 | 0.8905609 | -1.5702298 | 0.9373729 | -0.9589105 | 95.33037 | 78 | 0.0137570 | 0.0886976 |
| AcadSC_7rc | 0.8948377 | -1.5374508 | 0.8939398 | -1.8452567 | 73.69678 | 74 | 0.0000000 | 0.4880755 |
| AcadSC_8rc | 0.9574289 | -1.2357586 | 0.9596394 | -1.1942121 | 145.52925 | 109 | 0.0168956 | 0.0111361 |
| AcadSC_9rc | 0.8272627 | -2.0824669 | 0.9057011 | -1.4356420 | 88.62651 | 70 | 0.0150551 | 0.0657570 |
| Attain_3rc | 0.8248491 | -3.5129748 | 0.7991884 | -4.5515753 | 95.09032 | 70 | 0.0174731 | 0.0247303 |
| Attain_4 | 0.8281921 | -3.8941186 | 0.8294210 | -4.0057583 | 76.35291 | 70 | 0.0087923 | 0.2818165 |
| Attain_5 | 0.8827762 | -1.8759624 | 0.9153878 | -1.4547266 | 82.84614 | 71 | 0.0119213 | 0.1589242 |
| Attain_6 | 0.6744555 | -7.4512628 | 0.6936204 | -7.6782897 | 59.95878 | 66 | 0.0000000 | 0.6858984 |
| Attain_7 | 0.9854552 | -0.4671920 | 0.9822180 | -0.5754730 | 97.31106 | 86 | 0.0105845 | 0.1900709 |
| StatSC_1 | 0.9469441 | -1.0050758 | 0.9476705 | -1.1032146 | 121.36563 | 122 | 0.0000000 | 0.4991892 |
| StatSC_2 | 0.7898828 | -4.2473277 | 0.7966599 | -4.5179768 | 100.93881 | 102 | 0.0000000 | 0.5110969 |
| StatSC_3 | 0.8733246 | -2.1641293 | 0.9367211 | -1.1220970 | 147.51844 | 118 | 0.0145973 | 0.0340915 |
| StatSC_4rc | 0.7809108 | -3.7154255 | 0.8108177 | -4.3623962 | 108.43566 | 100 | 0.0084767 | 0.2652186 |
| StatSC_5rc | 0.8486758 | -2.5504583 | 0.9121291 | -1.7634856 | 134.04473 | 116 | 0.0115110 | 0.1206897 |
| StatSC_6 | 0.9352988 | -1.2699613 | 0.9627186 | -0.8021607 | 138.38401 | 144 | 0.0000000 | 0.6163476 |
| StatSC_7rc | 0.8968812 | -2.2054105 | 0.8760044 | -2.9107588 | 115.21881 | 110 | 0.0063570 | 0.3478142 |
| StatSC_8rc | 0.9031984 | -1.9813380 | 0.9045994 | -2.2687630 | 120.03544 | 119 | 0.0027224 | 0.4561557 |
| StatSC_9rc | 0.9056372 | -1.8125412 | 0.9636489 | -0.7427572 | 167.93364 | 130 | 0.0157655 | 0.0140235 |
| Difficult_1rc | 0.8909788 | -1.9600453 | 0.8999045 | -1.9586193 | 72.86696 | 63 | 0.0115501 | 0.1852302 |
| Difficult_2 | 0.9361260 | -1.6242493 | 0.9345141 | -1.7123319 | 87.94482 | 70 | 0.0147770 | 0.0723143 |
| Difficult_3 | 0.6972075 | -6.0852168 | 0.7280996 | -6.6251183 | 85.76426 | 53 | 0.0229471 | 0.0029304 |
| Difficult_6rc | 0.8405605 | -3.8083958 | 0.8579135 | -3.5524106 | 73.00161 | 61 | 0.0129456 | 0.1396281 |
| Difficult_7rc | 0.7289974 | -4.9178059 | 0.7621450 | -5.1911757 | 69.47166 | 54 | 0.0156220 | 0.0764665 |
| Expectancy_2 | 0.9674843 | -0.5328715 | 0.9497781 | -0.8692609 | 78.49411 | 77 | 0.0040655 | 0.4312087 |
| Expectancy_3 | 0.7855043 | -3.6931591 | 0.8642467 | -2.2655340 | 82.62984 | 69 | 0.0129714 | 0.1255846 |
| Expectancy_4 | 0.9126287 | -1.4695519 | 0.9364655 | -1.0767409 | 73.22474 | 76 | 0.0000000 | 0.5689218 |
| Expectancy_5 | 0.9230945 | -1.7690663 | 0.9208989 | -1.9118636 | 85.98018 | 94 | 0.0000000 | 0.7100119 |
| Expectancy_7 | 0.9860077 | -0.2870326 | 0.9552069 | -1.0227744 | 119.30105 | 93 | 0.0155207 | 0.0344049 |
| Expectancy_8 | 0.9241643 | -1.3000776 | 0.9138725 | -1.5748539 | 92.46814 | 83 | 0.0098573 | 0.2236424 |
| Expectancy_9 | 0.9236486 | -1.4927916 | 0.9101846 | -1.8772188 | 102.49405 | 89 | 0.0113643 | 0.1553410 |
| Expectancy_10 | 0.8902010 | -1.7003156 | 0.9289231 | -1.1898517 | 121.32323 | 91 | 0.0168474 | 0.0184993 |
| Cost_1 | 0.5941676 | -8.3828444 | 0.6151220 | -8.8057106 | 50.49347 | 47 | 0.0079569 | 0.3371768 |
| Cost_2 | 0.8301033 | -3.3262911 | 0.8109457 | -3.8626571 | 77.37900 | 49 | 0.0222109 | 0.0059971 |
| Cost_3rc | 1.0070825 | 0.1825691 | 0.9800951 | -0.4812412 | 76.52744 | 75 | 0.0041650 | 0.4292615 |
| Cost_4rc | 0.9612453 | -0.8691532 | 0.9338089 | -1.5476998 | 65.22785 | 68 | 0.0000000 | 0.5728432 |
| Cost_6 | 0.9054536 | -1.9991855 | 0.9066992 | -2.0979594 | 77.78479 | 63 | 0.0141385 | 0.0994654 |
| item | outfit | z.outfit | infit | z.infit | S_X2 | df.S_X2 | RMSEA.S_X2 | p.S_X2 |
|---|---|---|---|---|---|---|---|---|
| Belief_2rc | 0.5380197 | -12.9008757 | 0.5125231 | -14.4546993 | 73.30856 | 54 | 0.0174743 | 0.0412696 |
| Belief_4rc | 0.9891897 | -0.3267163 | 0.9876377 | -0.3764830 | 93.80026 | 60 | 0.0219334 | 0.0034412 |
| Belief_5rc | 0.9952998 | -0.1275334 | 0.9950669 | -0.1344265 | 64.97213 | 62 | 0.0063982 | 0.3735617 |
| Belief_10rc | 0.8657171 | -4.0312672 | 0.8688156 | -4.0202310 | 65.28083 | 57 | 0.0111384 | 0.2110809 |
| Attain_1rc | 0.9513506 | -1.2143176 | 0.9470148 | -1.3518452 | 79.45097 | 55 | 0.0194845 | 0.0171642 |
| Attain_2rc | 0.6114004 | -8.2235438 | 0.6401034 | -9.4286699 | 51.03996 | 47 | 0.0085676 | 0.3178680 |
| Attain_3rc | 0.6802487 | -6.2181098 | 0.6969834 | -6.6023848 | 82.90139 | 47 | 0.0255404 | 0.0009574 |
| Attain_4 | 0.8545637 | -3.5226468 | 0.8623666 | -3.4725524 | 56.40512 | 52 | 0.0085055 | 0.3137271 |
Now we plot tracelines.
Now we construct Wright Maps for Group 1.
Now we drop Belief 2, 4, 5, and 10.
## [1] "Belief"
##
Iteration: 1, Log-Lik: -10236.042, Max-Change: 1.89730
Iteration: 2, Log-Lik: -9996.770, Max-Change: 0.67992
Iteration: 3, Log-Lik: -9936.841, Max-Change: 0.24663
Iteration: 4, Log-Lik: -9914.178, Max-Change: 0.14474
Iteration: 5, Log-Lik: -9903.248, Max-Change: 0.13562
Iteration: 6, Log-Lik: -9897.638, Max-Change: 0.10366
Iteration: 7, Log-Lik: -9894.721, Max-Change: 0.08512
Iteration: 8, Log-Lik: -9893.091, Max-Change: 0.05911
Iteration: 9, Log-Lik: -9892.161, Max-Change: 0.02183
Iteration: 10, Log-Lik: -9891.828, Max-Change: 0.02016
Iteration: 11, Log-Lik: -9891.375, Max-Change: 0.01473
Iteration: 12, Log-Lik: -9891.137, Max-Change: 0.01089
Iteration: 13, Log-Lik: -9890.895, Max-Change: 0.00450
Iteration: 14, Log-Lik: -9890.870, Max-Change: 0.00301
Iteration: 15, Log-Lik: -9890.856, Max-Change: 0.00263
Iteration: 16, Log-Lik: -9890.837, Max-Change: 0.00207
Iteration: 17, Log-Lik: -9890.833, Max-Change: 0.00100
Iteration: 18, Log-Lik: -9890.832, Max-Change: 0.00078
Iteration: 19, Log-Lik: -9890.831, Max-Change: 0.00056
Iteration: 20, Log-Lik: -9890.831, Max-Change: 0.00036
Iteration: 21, Log-Lik: -9890.831, Max-Change: 0.00021
Iteration: 22, Log-Lik: -9890.831, Max-Change: 0.00017
Iteration: 23, Log-Lik: -9890.830, Max-Change: 0.00022
Iteration: 24, Log-Lik: -9890.830, Max-Change: 0.00008## Data does not contain missing values. Continuing normally## Sample size after row-wise response data removal: 1172## Data does not contain missing values. Continuing normally## Sample size after row-wise response data removal: 1172
Group 2 Wright Maps.
Now we drop Attain_7.
## [1] "Attain"
##
Iteration: 1, Log-Lik: -11774.892, Max-Change: 1.01678
Iteration: 2, Log-Lik: -11640.216, Max-Change: 0.85378
Iteration: 3, Log-Lik: -11602.052, Max-Change: 0.28053
Iteration: 4, Log-Lik: -11583.672, Max-Change: 0.21287
Iteration: 5, Log-Lik: -11576.236, Max-Change: 0.12501
Iteration: 6, Log-Lik: -11573.015, Max-Change: 0.10782
Iteration: 7, Log-Lik: -11570.243, Max-Change: 0.11848
Iteration: 8, Log-Lik: -11569.669, Max-Change: 0.05194
Iteration: 9, Log-Lik: -11569.382, Max-Change: 0.02579
Iteration: 10, Log-Lik: -11569.280, Max-Change: 0.02167
Iteration: 11, Log-Lik: -11569.199, Max-Change: 0.01558
Iteration: 12, Log-Lik: -11569.156, Max-Change: 0.01189
Iteration: 13, Log-Lik: -11569.109, Max-Change: 0.00335
Iteration: 14, Log-Lik: -11569.106, Max-Change: 0.00293
Iteration: 15, Log-Lik: -11569.105, Max-Change: 0.00500
Iteration: 16, Log-Lik: -11569.103, Max-Change: 0.00107
Iteration: 17, Log-Lik: -11569.102, Max-Change: 0.00022
Iteration: 18, Log-Lik: -11569.102, Max-Change: 0.00259
Iteration: 19, Log-Lik: -11569.102, Max-Change: 0.00086
Iteration: 20, Log-Lik: -11569.101, Max-Change: 0.00059
Iteration: 21, Log-Lik: -11569.101, Max-Change: 0.00031
Iteration: 22, Log-Lik: -11569.101, Max-Change: 0.00016
Iteration: 23, Log-Lik: -11569.101, Max-Change: 0.00055
Iteration: 24, Log-Lik: -11569.101, Max-Change: 0.00016
Iteration: 25, Log-Lik: -11569.101, Max-Change: 0.00011
Iteration: 26, Log-Lik: -11569.101, Max-Change: 0.00273
Iteration: 27, Log-Lik: -11569.101, Max-Change: 0.00039
Iteration: 28, Log-Lik: -11569.101, Max-Change: 0.00044
Iteration: 29, Log-Lik: -11569.101, Max-Change: 0.00009## Data does not contain missing values. Continuing normally## Sample size after row-wise response data removal: 1175## Data does not contain missing values. Continuing normally## Sample size after row-wise response data removal: 1175
Now we print tables of the Thurstonian Thresholds for the full IRT (without dropping any items).
## Item thur.b1 thur.b2 thur.b3 thur.b4 thur.b5
## 1 Belief_1 -2.5658771 -1.7590043 -1.266515385 -0.54101821 0.63155328
## 2 Belief_3rc -3.3021751 -2.4281971 -1.599055548 -1.02319017 -0.17425484
## 3 Belief_6 -2.9654232 -2.3309469 -1.800363005 -0.94369697 0.17009876
## 4 Belief_7 -3.3495683 -2.5372322 -2.050024353 -1.25220652 -0.27675759
## 5 Belief_8 -4.6370259 -3.7713983 -3.077528670 -2.17114017 -0.64154040
## 6 Belief_9 -2.7467633 -2.1137429 -1.662337413 -0.73415668 0.20991349
## 7 Intrinsic_1 -1.7930618 -1.1684843 -0.684660432 -0.11161104 0.73822854
## 8 Intrinsic_2 -2.2674681 -1.5043921 -1.028912471 -0.40871089 0.48211393
## 9 Intrinsic_3 -2.2570415 -1.4328364 -0.999739969 -0.27353717 0.61969758
## 10 Intrinsic_4 -2.1965583 -1.3686050 -0.870833903 -0.22792491 0.65526981
## 11 Intrinsic_5 -1.9999854 -1.2408798 -0.697240977 -0.00155098 0.92148049
## 12 Intrinsic_6 -1.4299482 -0.6034344 -0.084506850 0.54895758 1.36288038
## 13 Intrinsic_7 -2.3474732 -1.5375804 -1.085128232 -0.49696717 0.48538390
## 14 Extrinsic_1 -2.6982921 -1.7537461 -1.219030427 -0.58196013 0.46676887
## 15 Extrinsic_4 -2.2953042 -1.4260430 -0.895308255 -0.17694190 0.80507436
## 16 Extrinsic_5 -2.3207322 -1.4886624 -0.977598621 -0.36835122 0.54205087
## 17 Extrinsic_6 -1.9702883 -0.4920995 0.197113782 1.23150952 2.53882700
## 18 Extrinsic_7 -1.8183338 0.1952663 0.871315347 1.91338848 3.20070041
## 19 Extrinsic_8 -1.1520435 1.4297597 2.507406050 4.38257468 5.86264303
## 20 Utility_1 -2.2027968 -1.5541560 -1.139996385 -0.47745583 0.40346418
## 21 Utility_2 -2.9908434 -2.1375930 -1.530071537 -0.77898152 0.30900902
## 22 Utility_3rc -2.3826766 -1.9543346 -1.277472410 -0.68403816 -0.01051945
## 23 Utility_4 -2.6299883 -1.9427464 -1.488430014 -0.78476091 0.39559462
## 24 Utility_5rc -2.2929583 -1.6951772 -1.181082047 -0.57112115 0.17467872
## 25 Utility_6 -3.0254259 -2.0687187 -1.499479298 -0.66780478 0.50881135
## 26 Utility_7 -2.6245952 -1.6517254 -1.130619582 -0.22813003 0.92768852
## 27 Utility_8rc -3.1035632 -2.5022090 -1.770424385 -0.84750631 -0.23430892
## 28 Attain_5 -3.8573717 -3.0982139 -2.469779919 -1.76873341 -0.60630674
## 29 Attain_6 -1.8889477 -1.1278904 -0.721389748 -0.12650827 0.73816203
## 30 Attain_7 -3.6707922 -1.4411719 -0.441392413 0.65791952 2.34779903
## 31 Interest_1rc -1.3575360 -0.5388929 0.405679420 0.87784509 1.44833747
## 32 Interest_2 -1.5058684 -0.7560444 -0.264335579 0.28664540 1.03406725
## 33 Interest_3rc -1.3124386 -0.5711358 0.125753918 0.58115965 1.16910984
## 34 Interest_4 -1.6852040 -0.8137847 -0.340953876 0.28855395 1.14496813
## 35 Interest_5 -0.9246366 -0.2841907 0.198197794 0.74692566 1.45353893
## 36 Interest_6 -1.7512047 -0.9622286 -0.456032149 0.06946371 1.00459833
## 37 Interest_7rc -1.4283871 -0.5706606 0.163745794 0.71133770 1.36495502
## 38 Interest_8rc -1.3669907 -0.7974456 -0.200851529 0.38001169 0.83301209
## 39 Interest_9 -1.4587080 -0.5384727 -0.009001622 0.72462548 1.55905177
## thur.b6
## 1 2.0030669
## 2 1.2924869
## 3 1.5229117
## 4 1.1077984
## 5 1.2963095
## 6 1.5997355
## 7 1.8831100
## 8 1.6789959
## 9 1.7938769
## 10 1.8836178
## 11 2.1677658
## 12 2.4188763
## 13 1.7355342
## 14 1.7618592
## 15 2.0507009
## 16 1.5961227
## 17 4.3009686
## 18 4.9346944
## 19 7.5307426
## 20 1.5384891
## 21 1.7614740
## 22 1.0769370
## 23 1.7590945
## 24 1.3517284
## 25 2.0315166
## 26 2.4124099
## 27 0.8463854
## 28 1.0404742
## 29 1.7505387
## 30 4.2109482
## 31 2.6514122
## 32 1.9726461
## 33 2.0879580
## 34 2.1575654
## 35 2.3110526
## 36 2.0616872
## 37 2.3695542
## 38 1.8440287
## 39 2.7496425## Item thur.b1 thur.b2 thur.b3 thur.b4 thur.b5
## 1 AcadSC_1 -6.868874 -5.5667603 -4.91838786 -3.97304408 -2.90554402
## 2 AcadSC_2 -4.187392 -3.0394674 -1.98004249 -1.21944517 0.23448040
## 3 AcadSC_3 -4.431019 -3.3995194 -2.55701260 -1.89349207 -0.59856088
## 4 AcadSC_4 -3.980458 -3.0778043 -2.11879598 -1.19452879 0.08112571
## 5 AcadSC_5rc -3.466523 -2.1637710 -0.97082500 -0.40832689 0.45790244
## 6 AcadSC_6 -5.199197 -4.3425277 -3.31209012 -2.30908186 -1.15812124
## 7 AcadSC_7rc -2.955267 -2.4067372 -1.70124173 -1.15501850 -0.40551770
## 8 AcadSC_8rc -3.615423 -1.8431420 -0.18473196 0.47537041 1.66984943
## 9 AcadSC_9rc -3.255408 -2.7874386 -2.10231052 -1.54207977 -0.80964347
## 10 Attain_3rc -2.803979 -2.1288376 -1.29938271 -0.60193974 0.12932407
## 11 Attain_4 -2.740938 -1.7406733 -1.18233111 -0.06136894 0.97802501
## 12 Attain_5 -5.374913 -3.7622888 -3.02392913 -2.12510384 -0.80223388
## 13 Attain_6 -2.140406 -1.2744669 -0.79993947 -0.17165102 0.66059945
## 14 Attain_7 -6.762962 -2.4611750 -0.90579505 0.78975153 3.50199541
## 15 StatSC_1 -3.147248 -1.9863027 -1.22180976 -0.60334191 0.78669572
## 16 StatSC_2 -1.899537 -1.2176339 -0.63165085 0.08450225 1.07747400
## 17 StatSC_3 -5.152399 -3.4577901 -2.57286247 -1.82668687 -0.36765311
## 18 StatSC_4rc -1.512790 -0.8647754 -0.16405718 0.18896708 0.82342691
## 19 StatSC_5rc -2.642763 -2.0361271 -1.31601081 -0.69078211 -0.06367886
## 20 StatSC_6 -3.490907 -2.4087937 -1.61869277 -0.87681487 0.21547456
## 21 StatSC_7rc -2.111235 -1.3209732 -0.34794658 0.14994355 1.01674907
## 22 StatSC_8rc -1.593015 -0.5044445 0.39862681 0.86408295 1.54100835
## 23 StatSC_9rc -4.276312 -3.2833114 -1.91782257 -1.14897684 -0.04617113
## 24 Difficult_1rc -1.214422 0.1214875 1.31527299 2.01560939 2.81519631
## 25 Difficult_2 -2.881075 -1.5578485 -0.32211561 0.37440515 1.77697065
## 26 Difficult_3 -1.222122 -0.4194637 0.21936571 0.76740539 1.71885828
## 27 Difficult_6rc -2.441866 -1.2022296 -0.08059242 0.52931387 1.33142394
## 28 Difficult_7rc -1.148926 -0.1446473 0.71706569 1.12227028 1.75121973
## 29 Expectancy_2 -3.435214 -2.4786212 -1.76034507 -1.00140512 0.46220849
## 30 Expectancy_3 -3.593768 -2.6549370 -2.20299723 -1.36379143 -0.14977758
## 31 Expectancy_4 -3.869385 -2.9824659 -2.07195299 -1.43860667 0.04364822
## 32 Expectancy_5 -3.484202 -1.9305818 -1.00343610 -0.18925096 1.27837523
## 33 Expectancy_7 -3.302408 -2.1510744 -1.33587072 -0.38223478 0.96381114
## 34 Expectancy_8 -3.483295 -2.5046345 -1.77635043 -1.09208764 0.23278906
## 35 Expectancy_9 -3.227405 -2.2571611 -1.34253549 -0.57766240 0.87772658
## 36 Expectancy_10 -5.256579 -4.1793493 -3.21327144 -2.29208306 -0.85906883
## 37 Cost_1 -1.906663 -1.4078860 -0.82607443 -0.14804592 0.59444631
## 38 Cost_2 -2.644120 -1.9264084 -1.28872068 -0.58195834 0.35128627
## 39 Cost_3rc -2.377973 -0.6732168 0.65702980 1.88461371 2.96865899
## 40 Cost_4rc -2.085668 -1.1780827 -0.35996723 0.62837481 1.34852327
## 41 Cost_6 -2.001909 -1.2061949 -0.58899774 0.13575510 1.01171494
## thur.b6
## 1 -0.9777819
## 2 1.7698102
## 3 1.2616252
## 4 1.7085889
## 5 2.1595832
## 6 0.7197553
## 7 0.9563711
## 8 3.8637218
## 9 0.5684665
## 10 1.5946149
## 11 2.4671569
## 12 1.0457033
## 13 1.8628740
## 14 6.8095491
## 15 2.6440093
## 16 2.5016405
## 17 1.4487933
## 18 2.0648395
## 19 1.2351389
## 20 1.8050558
## 21 2.5578580
## 22 2.9335077
## 23 1.9959757
## 24 4.2194624
## 25 3.6984963
## 26 2.8178412
## 27 2.7683832
## 28 2.7069771
## 29 2.2539672
## 30 1.4468737
## 31 1.7159257
## 32 2.9245790
## 33 2.7947699
## 34 1.9137034
## 35 2.6275064
## 36 0.7748416
## 37 1.6790764
## 38 1.5633697
## 39 5.3585900
## 40 2.6251881
## 41 2.2126824Now we print the coefficients.
## a1 d1 d2 d3 d4 d5
## Belief_1 1.9253035 4.9400920 3.3866171 2.43842645 1.041624227 -1.2159317
## Belief_3rc 1.5389664 5.0819366 3.7369138 2.46089276 1.574655294 0.2681723
## Belief_6 2.0732219 6.1479803 4.8325703 3.73255204 1.956493236 -0.3526525
## Belief_7 2.0269016 6.7892453 5.1427198 4.15519757 2.538099348 0.5609604
## Belief_8 1.2813343 5.9415805 4.8324222 3.94334318 2.781956467 0.8220277
## Belief_9 2.0324786 5.5827375 4.2961370 3.37866516 1.492157709 -0.4266447
## Intrinsic_1 2.4529986 4.3983781 2.8662903 1.67947107 0.273781718 -1.8108736
## Intrinsic_2 1.9585800 4.4410176 2.9464722 2.01520737 0.800492977 -0.9442587
## Intrinsic_3 2.5811649 5.8257962 3.6983871 2.58049369 0.706044544 -1.5995416
## Intrinsic_4 2.3674229 5.2001824 3.2400667 2.06163210 0.539594638 -1.5513007
## Intrinsic_5 2.3253321 4.6506303 2.8854577 1.62131682 0.003606543 -2.1427481
## Intrinsic_6 2.1156681 3.0252958 1.2766669 0.17878844 -1.161412030 -2.8834025
## Intrinsic_7 2.1665513 5.0859211 3.3312469 2.35098600 1.076704871 -1.0516091
## Extrinsic_1 1.8677269 5.0396727 3.2755186 2.27681589 1.086942578 -0.8717968
## Extrinsic_4 2.1467938 4.9275449 3.0614204 1.92204224 0.379857781 -1.7283287
## Extrinsic_5 2.5661552 5.9553590 3.8201389 2.50866980 0.945246395 -1.3909867
## Extrinsic_6 1.1101699 2.1873548 0.5463140 -0.21882979 -1.367184824 -2.8185294
## Extrinsic_7 0.7536383 1.3703660 -0.1471602 -0.65665662 -1.442002847 -2.4121704
## Extrinsic_8 0.5978452 0.6887436 -0.8547749 -1.49904055 -2.620101025 -3.5049527
## Utility_1 2.4030272 5.2933806 3.7346793 2.73944236 1.147339354 -0.9695354
## Utility_2 1.5667672 4.6859553 3.3491105 2.39726589 1.220482692 -0.4841452
## Utility_3rc 2.5427461 6.0585416 4.9693766 3.24828803 1.739335396 0.0267483
## Utility_4 2.0661300 5.4338979 4.0139667 3.07528996 1.621418086 -0.8173499
## Utility_5rc 2.2359537 5.1269486 3.7903377 2.64084472 1.277000428 -0.3905735
## Utility_6 1.5903880 4.8116011 3.2900655 2.38475390 1.062068711 -0.8092075
## Utility_7 1.5772154 4.1395519 2.6051267 1.78323060 0.359810200 -1.4631646
## Utility_8rc 1.7487403 5.4273260 4.3757137 3.09601243 1.482068421 0.4097455
## Attain_5 1.1714942 4.5188886 3.6295397 2.89333288 2.072060944 0.7102848
## Attain_6 2.1900968 4.1369784 2.4701892 1.57991341 0.277065353 -1.6166463
## Attain_7 0.7236812 2.6564834 1.0429490 0.31942741 -0.476124009 -1.6990581
## Interest_1rc 1.7522446 2.3787351 0.9442722 -0.71084959 -1.538199361 -2.5378416
## Interest_2 2.8062974 4.2259146 2.1216853 0.74180424 -0.804412222 -2.9019002
## Interest_3rc 3.0437762 3.9947694 1.7384096 -0.38276678 -1.768919912 -3.5585087
## Interest_4 2.3171245 3.9048273 1.8856403 0.79003257 -0.668615423 -2.6530337
## Interest_5 3.5817560 3.3118228 1.0179019 -0.70989615 -2.675305497 -5.2062218
## Interest_6 2.4937838 4.3671260 2.3995902 1.13724560 -0.173227471 -2.5052511
## Interest_7rc 2.0128734 2.8751624 1.1486674 -0.32959955 -1.431832733 -2.7474817
## Interest_8rc 2.3040071 3.1495562 1.8373203 0.46276335 -0.875549626 -1.9192658
## Interest_9 2.0619484 3.0077805 1.1103028 0.01856088 -1.494140313 -3.2146842
## d6
## Belief_1 -3.856512
## Belief_3rc -1.989094
## Belief_6 -3.157334
## Belief_7 -2.245398
## Belief_8 -1.661006
## Belief_9 -3.251428
## Intrinsic_1 -4.619266
## Intrinsic_2 -3.288448
## Intrinsic_3 -4.630292
## Intrinsic_4 -4.459320
## Intrinsic_5 -5.040775
## Intrinsic_6 -5.117539
## Intrinsic_7 -3.760124
## Extrinsic_1 -3.290672
## Extrinsic_4 -4.402432
## Extrinsic_5 -4.095899
## Extrinsic_6 -4.774806
## Extrinsic_7 -3.718975
## Extrinsic_8 -4.502218
## Utility_1 -3.697031
## Utility_2 -2.759820
## Utility_3rc -2.738377
## Utility_4 -3.634518
## Utility_5rc -3.022402
## Utility_6 -3.230900
## Utility_7 -3.804890
## Utility_8rc -1.480108
## Attain_5 -1.218909
## Attain_6 -3.833849
## Attain_7 -3.047384
## Interest_1rc -4.645923
## Interest_2 -5.535832
## Interest_3rc -6.355277
## Interest_4 -4.999348
## Interest_5 -8.277627
## Interest_6 -5.141402
## Interest_7rc -4.769613
## Interest_8rc -4.248655
## Interest_9 -5.669621## a1 d1 d2 d3 d4 d5
## AcadSC_1 0.9327354 6.406842 5.1923145 4.5875545 3.70579892 2.71010381
## AcadSC_2 1.4498134 6.070938 4.4066606 2.8706922 1.76796801 -0.33995283
## AcadSC_3 1.6139382 7.151392 5.4866143 4.1268603 3.05597918 0.96604026
## AcadSC_4 1.4307153 5.694903 4.4034618 3.0313939 1.70903067 -0.11606780
## AcadSC_5rc 1.3710745 4.752861 2.9666913 1.3310734 0.55984659 -0.62781836
## AcadSC_6 1.2271753 6.380326 5.3290428 4.0645153 2.83364828 1.42121781
## AcadSC_7rc 2.4653915 7.285891 5.9335495 4.1942270 2.84757283 0.99975990
## AcadSC_8rc 0.8626157 3.118721 1.5899233 0.1593527 -0.41006199 -1.44043837
## AcadSC_9rc 2.2631641 7.367522 6.3084310 4.7578738 3.48997966 1.83235608
## Attain_3rc 1.6630726 4.663220 3.5404115 2.1609677 1.00106947 -0.21507532
## Attain_4 1.4945447 4.096455 2.6015141 1.7670467 0.09171863 -1.46170210
## Attain_5 1.0231909 5.499562 3.8495395 3.0940566 2.17438682 0.82083837
## Attain_6 2.0278721 4.340469 2.5844559 1.6221749 0.34808630 -1.33961118
## Attain_7 0.4441940 3.004067 1.0932392 0.4023487 -0.35080290 -1.55556538
## StatSC_1 1.5864720 4.993021 3.1512138 1.9383670 0.95718507 -1.24807077
## StatSC_2 2.6617187 5.056034 3.2409989 1.6812769 -0.22492123 -2.86793268
## StatSC_3 1.2567794 6.475429 4.3456794 3.2335206 2.29574248 0.46205887
## StatSC_4rc 2.8804994 4.357590 2.4909850 0.4725666 -0.54431954 -2.37188072
## StatSC_5rc 2.1061126 5.565955 4.2883128 2.7716669 1.45486487 0.13411484
## StatSC_6 1.2342336 4.308594 2.9730140 1.9978449 1.08219433 -0.26594593
## StatSC_7rc 2.2386327 4.726280 2.9571738 0.7789246 -0.33566853 -2.27612771
## StatSC_8rc 1.7994247 2.866511 0.9077098 -0.7172989 -1.55485220 -2.77292848
## StatSC_9rc 1.1979285 5.122717 3.9331723 2.2974143 1.37639210 0.05530972
## Difficult_1rc 1.5772565 1.915455 -0.1916170 -2.0745228 -3.17913294 -4.44028658
## Difficult_2 1.2495426 3.600026 1.9465981 0.4024972 -0.46783518 -2.22040054
## Difficult_3 2.5884184 3.163362 1.0857475 -0.5678102 -1.98636619 -4.44912433
## Difficult_6rc 1.8235849 4.452950 2.1923678 0.1469671 -0.96524878 -2.42796459
## Difficult_7rc 2.5313794 2.908367 0.3661572 -1.8151653 -2.84089191 -4.43300159
## Expectancy_2 1.8626684 6.398664 4.6168492 3.2789391 1.86528563 -0.86094112
## Expectancy_3 2.1225974 7.628122 5.6353624 4.6760761 2.89478011 0.31791749
## Expectancy_4 1.7212294 6.660100 5.1335081 3.5663064 2.47617212 -0.07512859
## Expectancy_5 1.3492331 4.701000 2.6048049 1.3538692 0.25534367 -1.72482619
## Expectancy_7 1.1946574 3.945246 2.5697970 1.5959078 0.45663961 -1.15142412
## Expectancy_8 1.6838797 5.865451 4.2175032 2.9911605 1.83894421 -0.39198878
## Expectancy_9 1.5346904 4.953068 3.4640434 2.0603764 0.88653296 -1.34703858
## Expectancy_10 1.0255559 5.390915 4.2861562 3.2953894 2.35065923 0.88102309
## Cost_1 3.8835484 7.404616 5.4675936 3.2081000 0.57494351 -2.30856103
## Cost_2 2.7238615 7.202218 5.2472696 3.5102966 1.58517389 -0.95685515
## Cost_3rc 0.9505766 2.260445 0.6399442 -0.6245571 -1.79146966 -2.82193772
## Cost_4rc 1.7480508 3.645854 2.0593484 0.6292410 -1.09843111 -2.35728723
## Cost_6 2.2274619 4.459176 2.6867533 1.3119700 -0.30238931 -2.25355650
## d6
## AcadSC_1 0.9120118
## AcadSC_2 -2.5658946
## AcadSC_3 -2.0361851
## AcadSC_4 -2.4445043
## AcadSC_5rc -2.9609495
## AcadSC_6 -0.8832660
## AcadSC_7rc -2.3578292
## AcadSC_8rc -3.3329072
## AcadSC_9rc -1.2865330
## Attain_3rc -2.6519603
## Attain_4 -3.6872762
## Attain_5 -1.0699541
## Attain_6 -3.7776702
## Attain_7 -3.0247609
## StatSC_1 -4.1946469
## StatSC_2 -6.6586633
## StatSC_3 -1.8208136
## StatSC_4rc -5.9477689
## StatSC_5rc -2.6013415
## StatSC_6 -2.2278605
## StatSC_7rc -5.7261046
## StatSC_8rc -5.2786263
## StatSC_9rc -2.3910361
## Difficult_1rc -6.6551744
## Difficult_2 -4.6214287
## Difficult_3 -7.2937518
## Difficult_6rc -5.0483818
## Difficult_7rc -6.8523861
## Expectancy_2 -4.1983934
## Expectancy_3 -3.0711302
## Expectancy_4 -2.9535018
## Expectancy_5 -3.9459388
## Expectancy_7 -3.3387926
## Expectancy_8 -3.2224464
## Expectancy_9 -4.0324089
## Expectancy_10 -0.7946433
## Cost_1 -6.5207743
## Cost_2 -4.2584025
## Cost_3rc -5.0937502
## Cost_4rc -4.5889623
## Cost_6 -4.9286657